Interference Cancellation in Overlay Cognitive Radio Based on OFDM Using Nonlinear Kalman-Filter for Channel Estimation

Cognitive radio (CR) has been proposed as a technology to improve the spectrum efficiency. We consider an overlay CR consisting of a primary macro-cell and cognitive small cells of cooperative secondary base stations (SBS). We suggest studying a CR where an orthogonal frequency division multiplexing (OFDM) is used for both the primary users (PU) and the secondary users (SU). In order to cancel the interferences, zero forcing beamforming (ZFBF) is considered. However, applying ZFBF depends on the channels between the SBS and the PU. A channel estimation is hence necessary. For this purpose, we propose to approximate the channel by an autoregressive process (AR) and to consider the channel estimation issue by using a training sequence. In that case, the AR parameters and the channel can be jointly estimated from the received noisy signal by using a recursive approach. Nevertheless, the corresponding state space representation of the system is non-linear. Then, we propose to carry out a complementary study by compare non-linear Kalman filter based approaches.